Exercise

# Normalize the variables

Now, for the last step in data preparation. You will transform the unskewed dataset `wholesale_boxcox`

to the same scale, meaning all columns have a mean of zero, and standard deviation of 1. You will use the `StandardScaler`

function from the `sklearn.preprocessing`

module.

The unskewed `wholesale_coxbox`

dataset you have transformed in the previous exercise has been imported as a `pandas`

DataFrame. Also, the `StandardScaler()`

instance has been initialized as `scaler`

.

Instructions

**100 XP**

- Fit the initialized
`scaler`

instance on the Box-Cox transformed dataset. - Transform and store the scaled dataset as
`wholesale_scaled`

. - Create a
`pandas`

DataFrame from the scaled dataset. - Print the mean and standard deviation for all columns.